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Introduction to Prioritization Scores

How to use quantitative scoring systems to prioritize your product roadmap

Jordan Duff avatar
Written by Jordan Duff
Updated over a week ago


Product teams have no shortage of ideas and inputs for how to enhance their product. That can make roadmap prioritization very challenging. In order to help minimize subjectivity, which can lead product teams to waste time and effort building ultimately unsuccessful new products and features, many different prioritization methods have sprung up. Most try to incorporate some degree of quantitative scoring.

Most product managers agree that these scoring systems need to be used carefully, primarily because even skilled product experts are bad at correctly estimating both the work required to build and ship the product/feature and the amount of value it will provide to users. Former Google PM Itamar Gilad says, “Time after time I see managers and teams trusting their gut feeling when assessing future impact, irrespective of how well past predictions performed.”

Using scores in combination with product discovery

There is a way for product teams to get better at estimating value. It's through a sustained commitment to product discovery, the due diligence of collecting real market feedback and data to support any given product idea. This is especially effective when combined with quantitative scoring of ideas in the backlog. Here's how that might work.

  • Enable one or more of the scoring scoring mechanisms in GLIDR (our team uses RICE and Pain vs Frequency).

  • Score new ideas as they come in (our team gathers ideas in the New column of the Status grouping. Once they are processed and scored, we move them to a column called Candidate.

  • Filter by score to find the ideas that are worth spending time on. Prioritize the highest potential ideas for discovery work. 

  • Use the evidence added during discovery to decide what advances through your stages of development and eventually makes it into production. 

In this way, scoring supports initial prioritization, but you make you decisions about what to ship based on real customer data. This allows you to avoid some of the most common pitfalls of scoring. When a product team or company commits to this process over time, they can begin to see how accurate their estimations of both work required and customer impact are. They can also focus on “prioritizing opportunities, not solutions” as Teresa Torres phrases it.

GLIDR supports these scoring frameworks:

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